The Status of Health Care Medical Supply Inventory Systems
Current Trends in Medical Supply Inventory
Inventory is utilized in forecasting different budgets through placing consideration on the current equipment values, performing the needs assessment and determining the lifetime of different equipment (Coleman et al., 2015). On average, a hospital’s yearly budget is directed towards purchasing medical supplies and materials that include medicines (Böhme et al., 2014). According to Böhme et al. (2014), the increasing costs of medical supplies and drugs have directly affected the expenses of the hospital. Therefore, the researchers concluded that inventory management has been developed in a manner that is cost effective which guarantees supply of products to every department (Böhme et al., 2014). Nonetheless, it has been noted by Bhakoo & Choi (2013) that overstocking leads to more financial issues and time has be allocated to resolve them. At the same time, the researchers assume that if there is shortage of medical supply then medical processes are delayed which may lead to medication error. It is important to avoid overstocking or under stocking of medical supplies.
Normally, medical supply inventory entails high variation and medical supplies that makes inventory management difficult especially when it comes to tracking each item. Furthermore, medical supplies are classified through the ABC analysis that majorly gives more priority to special items; once the special items are located they are forecasted through the demand forecasting technique (Bhakoo & Choi, 2013). Demand forecasting is used to control inventory and is majorly used in the health care setting so that it can determine future demand (Landry & Beaulieu, 2013). It is important to note that forecasting appropriate demand for the medical and drug supplies is hard mostly due to absence of accurate data for the consumption of medical supplies (Eckelman & Sherman, 2016).
According to Dobrzykowski et al. (2014), the Vendor Managed Inventory (VMI) was adopted in the medical supply inventory systems in which the institution was responsible for the management of inventory and taking decisions concerning replenishment. This is meant to define the information requirements when it comes to stockless inventory systems. Alternatively, it is indicated that VMI normally requires precise information on the current stock levels but it is a challenge trying to provide the information in hospitals (Eckelman & Sherman, 2016). This method of inventory leads to less administration in hospitals, minimal errors, enhanced information reliability and reduced inventory. However, Chen Chen et al. (2013) believe that this method is not efficient because more stock was being held and additional benefits were eliminated.
Forecasting In Medical Supply Inventory Systems
There are several forecasting models that can be utilized when it comes to medical supply inventory and selecting the most appropriate method requires correct definitions of the inputs that are available to guarantee the process, environmental factors that may affect the process and the desired output (Foshay & Kuziemsky, 2014). In this case, Landry & Beaulieu (2013) point out that inputs entail aspects like marketing research and demand history, knowledge of the special situations that may affect historical data and the availability of knowledgeable opinions from personnel. On the other hand, Eckelman & Sherman (2016) believe that outputs include timing of the expected demand that is defined by the region, customer and product. The constraints may involve management policies, market conditions, technology and available resources (Landry & Beaulieu, 2013).
Different researchers offer alternate classification schemes when it comes to categorizing forecasting techniques. For instance, Landry & Beaulieu (2013) presented the qualitative forecasting procedure that is used in cases where new products are available within the market. This includes forecasts that are based on experience and judgment. On the other hand, Wamba et al., (2013) point out that quantitative technique are mathematically based and need sufficient quantities of precise data for successful application. Many of the forecasts entail data that occurs in a time series.
In health care facilities, each unit possesses inventory review policy and some of them use the periodic review policy and continuous review policy (Krichanchai et al., 2017). In medical warehouses, data gathering is limited because they use periodic review policy (Machado Guimarães et al., 2013). Normally, medical warehouses order new stock each month to the supplier. Furthermore, Krichanchai et al. (2017) indicates that the amount of the order quantity does not rely on forecast but on the demand of the previous month. This is because a lead-time of the distribution of goods from a supplier normally takes a day. Moreover, large inventories tend to consume more cash, increase investments and may lead to bankruptcy if it is not controlled efficiently (Machado Guimarães et al., 2013).
It is important to note that medical supply inventory management focuses on cost containment and enhances efficiency (Unger & Landis, 2016). Inventory control is essential when there are scarce resources and hospitals have to make sure that there is optimum utilization of the available resources in order to offer better patient care (Uthayakumar & Priyan, 2013). Unger & Landis (2016) also found that hospital management faces the alternative of selecting the right aspects that will reduce inventory cost. Hence, rational inventory management techniques have to be applied in order to maximize on the budget meant for enhanced care for the patients.
Inventory Centralization
Health care organizations normally have advanced warehouses that contain clinical consumption materials for every utilization service. Furthermore, Dobrzykowski et al. (2014) believe that it increases inventory investment levels because the number of services continuously reinstalls it. The same finding was realized by Privett & Gonsalvez (2014) who indicated that the vendor-managed inventory is an integrated approach that requires a supplier to decide on an accurate inventory level of every product and the right inventory policies to coincide with all levels. Therefore, medical suppliers monitor inventory levels of the buyers or patients which leads to precise information exchange among customers and suppliers; this plays an important role in the implementation of vendor-managed inventory (VMI) (Privett & Gonsalvez, 2014).
Medical institutions also adopt the Electronic Data Interchange (EDI) because it is appropriate for information exchange. Most of the information included in this technique is provided through spreadsheets or fax (Eckelman & Sherman, 2016). This system is suitable for reducing the inventory costs and this influences the supply chain because suppliers could control the costs of the stocks. Alternatively, Lavis et al. (2015) assume that the optimal management of inventories allows substantial savings within the health care field. They translate this to mean that if effective approaches are utilized, the medical suppliers can reduce costs of care while reducing the service levels provided to the population. However, Eckelman & Sherman (2016) conclude their findings by showing that identification and implementation of the right techniques is fundamental to a hospital’s ability to pursuit efficient operations yield and cost effective.
Health care institutions have realized that it is fundamental to implement the information system so that under stock can be indicated and a prompt reorder applied for medical appliances in stock; this will create the continuous circle which will abolish empirical management (Niles, 2016). The health care sector focuses on inventory management as well as distribution because it determines the success of their activities and the services they offer patients. Many of the hospital inventories do not just include medicines but also medical devices as well as consumable goods like bandages, syringes, and many more (Eckelman & Sherman, 2016).
Trends of Inventory Control in Medical Supply
The rate of health care spending in many developed nations has significantly outpaced the rise in Inflation levels, the GDP growth rate and the population increase. For instance, health care spending in the US stood at two trillion dollars or $6, 697 per capita or 16 percent of the GDP and this figure is expected to rise and reach over 30 percent of the GDP by the 2020’s (Krichanchai et al., 2017). Krichanchai et al. (2017) found that other than putting a strain on the economy and taking up money that could have otherwise been used for other developmental projects, increasing health care cost also takes money away from the common citizens leaving them with less money for expenditure.
The situation is not different in developing countries as the rise expenditure of health care is causing governments to borrow heavily (Privett & Gonsalvez, 2014). Moreover, many governments have increased their taxes to fund for the rise in health care cost which is majorly contributed by poor inventory control practices. Sarker (2014) has proposed new measures that can help reduce the rising cost of healthcare can go a long way in free up funds that can be used to develop other key economic segments and improve the quality of care. Medical supply inventory system is applied in a spectrum of applications like customer relationship management, enhanced quality of care, medicine analysis and engineering, web mining, mobile computing and expert prediction. Furthermore, healthcare institutions utilize appropriate information systems for inventory control to produce effective medical reports on patients such as financial statements and volume related statements (Unger & Landis, 2016).
The inventory control tools used in healthcare also act as the means of saving time and related complexities (Wager et al., 2017). In this respect, some of the inventory control tasks include prediction and classification, association rule, clustering and patterns of medical information. Uthayakumar & Priyan (2013) believe that as a result of such actions inventory control applications in healthcare may assist in expanding health coverage to more people and give financial assistance that will minimize out of pocket expenditure.
Devices such as the IoT have revolutionized the healthcare sector by collecting large quantities of data that aid health care practitioners to utilize the inventory management applications to improve patient care (Uthayakumar & Priyan, 2013). Additionally, Holm et al. (2015) imply that data analytics and data management in medical inventories are also utilized to engender the deluge of data that exists; this makes it easier to understand the stock levels and identify areas that need to be restocked.
Currently, the healthcare industry generates complex data in large amounts which entails details on patients, disease diagnosis, hospital resources, medical devices, electronic patient records and so on. Landry & Beaulieu (2013) prove that the increased amounts of data show that they are the main resource when it comes to being analyzed and processed for knowledge extraction that enables support for effective decision making and cost savings. Furthermore, the inventory management applications applied in healthcare is grouped into broader categories that include: healthcare management, fraud and abuse and customer relationship management (Dobrzykowski et al., 2014).
It is important to have a business understanding of inventory management applications because it reinforces health care objectives and this could eventually lead to formation of successful criteria that can be applied to different inventory management procedures (Privett & Gonsalvez, 2014). Furthermore, predictive modeling is seen as the most popular form of enhancing inventory management because it predicts the target variable which is usually categorical; this may include prediction of a stock level (Sarker, 2014). Hence, the inventory control applications particularly in healthcare may present immense usefulness and potential for the healthcare workforce. Nonetheless, Holm et al. (2015) argue that in order for healthcare supply inventory systems to be successful, clean healthcare data must be available. It is important for the healthcare industry to determine how inventory data could be collected, prepared, stored and mined effectively (Holm et al., 2015). This may require standardization of the clinical vocabulary and sharing data among healthcare organizations in order to improve the applications of healthcare inventory management.
According to Lavis et al. (2015), inventory management applications could be developed within the healthcare industry so that usage patterns, preferences, future and current requirements of people can be improved to a satisfactory level; this means that inventory control skills would improve on a gradual basis. Moreover, the applications may also be utilized to predict the other products which the healthcare customer may utilize (this applies if a patient has a high probability to go along with a prescribed treatment or if preventive care has the ability to produce sufficient reduction in the future utilization).
Sarker (2014) adds that through inventory management applications, associations such as the Customer Potential Management Corporation have established the Consumer Healthcare Utilization Index which gives the indication of propensity of an individual to use particular healthcare services. He defined this by using 25 main diagnostic categories, particularly medical service areas or chosen diagnostic related groups. Furthermore, the index was based on many healthcare transactions of millions of patients and it can identify the patients that can gain more advantage from particular health services or products, continuous refined messages and channels utilized to reach prospective audiences for enhanced long-term patient loyalty and relationships.
Landry & Beaulieu (2013) suggest that applying inventory management applications to the patient survey data may assist in setting reasonable expectations about the stock levels, show alternative methods of improving service as well as provide sufficient knowledge on what the patients need from healthcare providers. In addition, Eckelman & Sherman (2016) suggest that inventory control within healthcare may assist to promote the disease education, wellness and prevention services by ensuring appropriate and relevant stocks are available. Coleman et al. (2015) report that Florida Hospital utilized appropriate inventory techniques in order to segment the Medicare patients and develop the commercial applications, which enable debt collection, analysis of the financial data and credit scoring.
Furthermore, the health industry believes that health advancements like IoT are a platform that includes more than just collecting data and improving inventory procedures (Privett & Gonsalvez, 2014). Nonetheless, inventory applications from such a device may simplify the manner in which health suppliers handle stocks. The capability of devices such as these enables the gradual monitoring stocks while leveraging the data through inventory control. Additionally, this platform is able to collect, distinguish and store important data that can be essential for effective inventory management processes.
Chen et al. (2013) believe that the pharmaceutical companies could benefit from inventory control by tracking the physicians that prescribe particular drugs and find out why they have prescribed them in order to predict stocks. This may help decide who should be targeted, reveal the most effective and least expensive treatment plan for any ailment, assist to identify physicians that practice particular clinical trials, and map an epidemic’s course so that pharmaceutical patients, physicians and salespersons can be supported.
Sarker (2014) believes that healthcare inventory management may be limited by data accessibility because raw inputs from data mining usually exist in alternate systems and settings like clinics, administration and so on. Therefore, in order to assist healthcare management, the inventory control applications could be established to improve identification and tracking of the areas that need re-stocking as well as identify instances of overstocking, reduce the amount of hospital claims and admissions and design effective interventions. For instance, Blue Cross healthcare facility implements inventory control initiatives in order to enhance outcomes as well as reduce expenditures through improved disease management (Chen et al., 2013). Furthermore, inventory management applications may be utilized to understand and identify the high cost stocks (Böhme et al., 2014).
It is believed that the healthcare organizations that adopt appropriate inventory management techniques have to make substantial investments of their resources including money, effort and time (Chen et al., 2013). However, Foshay & Kuziemsky (2014) claim that certain inventory management techniques could fail depending on a range of reasons like absence of management support, poor project management, lack of data mining expertise etc. It is important to note that inventory control needs intensive technological preparation and planning of work. Additionally, healthcare practitioners need to be convinced of how important and useful inventory management is so that they can possess the will to change their work processes (Chen et al., 2013). Furthermore, all of the parties that take part in promoting inventory control must cooperate and collaborate.
Böhme et al. (2014) indicates that inventory is utilized in forecasting different budgets through placing consideration on the current equipment values, performing the needs assessment and determining the lifetime of different equipment. On average, a hospital’s yearly budget is directed towards purchasing medical supplies and materials that include medicines (Böhme et al., 2014). The increasing costs of medical supplies and drugs have directly affected the expenses of the hospital. Therefore, inventory management has been developed in a manner that is cost effective which guarantees supply of products to every department (Holm et al., 2015). Nonetheless, it has been noted that overstocking leads to more financial issues and more time has be allocated to resolve them (Niles, 2016). At the same time, if there is shortage of medical supply then medical processes are delayed which may lead to medication error. It is important to avoid overstocking or under stocking of medical supplies.
Optimal management of inventories allows substantial savings within the health care field. If effective approaches are utilized, the medical suppliers can reduce costs of care while reducing the service levels provided to the population (Holm et al., 2015). Identification and implementation of the right techniques is fundamental to a hospital’s ability to pursuit efficient operations yield and cost effective. Inventory control is essential when there are scarce resources and hospitals have to make sure that there is optimum utilization of the available resources in order to offer better patient care (Uthayakumar & Priyan, 2013). Normally, hospital management faces the alternative of selecting the right aspects that will reduce inventory cost. Hence, rational inventory management techniques have to be applied in order to maximize on the budget meant for enhanced care for the patients (Privett & Gonsalvez, 2014). Health care institutions have realized that it is fundamental to implement the information system so that under stock can be indicated and a prompt reorder applied for medical appliances in stock; this will create the continuous circle which will abolish empirical management (Niles, 2016). Niles (2016) finally concludes that the health care sector focuses on inventory management as well as distribution because it determines the success of their activities and the services they offer patients.

References
Bhakoo, V., & Choi, T. (2013). The iron cage exposed: Institutional pressures and heterogeneity across the healthcare supply chain. Journal of Operations Management, 31(6), 432-449. Retrieved from https://asu.pure.elsevier.com/en/publications/the-iron-cage-exposed-institutional-pressures-and-heterogeneity-a
Böhme, T., Williams, S., Childerhouse, P., Deakins, E., & Towill, D. (2014). Squaring the circle of healthcare supplies. Journal of health organization and management, 28(2), 247-265. Retrieved from https://www.ncbi.nlm.nih.gov/pubmed/25065113
Chen, D. Q., Preston, D. S., & Xia, W. (2013). Enhancing hospital supply chain performance: A relational view and empirical test. Journal of Operations Management, 31(6), 391-408. Retrieved from https://pdfs.semanticscholar.org/308a/3136970504efe1ec23988608f639d7b8a767.pdf
Coleman, C. N., Sullivan, J. M., Bader, J. L., Murrain-Hill, P., Koerner, J. F., Garrett, A. L., … & Whitcomb, R. C. (2015). Public health and medical preparedness for a nuclear detonation: the nuclear incident medical enterprise. Health physics, 108(2), 149. Retrieved from http://europepmc.org/abstract/med/25551496
Dobrzykowski, D., Deilami, V. S., Hong, P., & Kim, S. C. (2014). A structured analysis of operations and supply chain management research in healthcare (1982–2011). International Journal of Production Economics, 147, 514-530. Retrieved from https://www.researchgate.net/publication/264158493_A_structured_analysis_of_operations_and_supply_chain_management_research_in_healthcare_1982-2011
Eckelman, M. J., & Sherman, J. (2016). Environmental impacts of the US health care system and effects on public health. PloS one,11(6), e0157014. Retrieved from http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0157014
Foshay, N., & Kuziemsky, C. (2014). Towards an implementation framework for business intelligence in healthcare. International Journal of Information Management, 34(1), 20-27. Retrieved from https://pdfs.semanticscholar.org/1c1f/5288338bc899cb664c0722d1997ec7cda32d.pdf
Holm, M. R., Rudis, M. I., & Wilson, J. W. (2015). Medication supply chain management through implementation of a hospital pharmacy computerized inventory program in Haiti.Global health action, 8(1), 26546. Retrieved from https://www.ncbi.nlm.nih.gov/pubmed/25623613
Krichanchai, S., Krichanchai, S., MacCarthy, B. L., & MacCarthy, B. L. (2017). The adoption of vendor managed inventory for hospital pharmaceutical supply. The International Journal of Logistics Management, 28(3), 755-780. Retrieved from http://www.emeraldinsight.com/doi/abs/10.1108/IJLM-01-2015-0010
Landry, S., & Beaulieu, M. (2013). The challenges of hospital supply chain management, from central stores to nursing units. Handbook of Healthcare Operations Management (pp. 465-482). Springer New York. Retrieved from https://link.springer.com/chapter/10.1007/978-1-4614-5885-2_18
Lavis, J. N., Wilson, M. G., Moat, K. A., Hammill, A. C., Boyko, J. A., Grimshaw, J. M., & Flottorp, S. (2015). Developing and refining the methods for a ‘one-stop shop’for research evidence about health systems. Health research policy and systems, 13(1), 10. Retrieved from https://www.ncbi.nlm.nih.gov/pubmed/25971248
Machado Guimarães, C., Crespo de Carvalho, J., & Maia, A. (2013). Vendor managed inventory (VMI): evidences from lean deployment in healthcare. Strategic Outsourcing: An International Journal, 6(1), 8-24. Retrieved from http://www.emeraldinsight.com/doi/abs/10.1108/17538291311316045?mbSc=1&fullSc=1&journalCode=so
Niles, N. J. (2016). Basics of the US health care system. Jones & Bartlett Learning. Retrieved from https://www.amazon.com/Basics-U-S-Health-Care-System/dp/1284120139
Privett, N., & Gonsalvez, D. (2014). The top ten global health supply chain issues: Perspectives from the field. Operations Research for Health Care, 3(4), 226-230. Retrieved from https://wagner.nyu.edu/impact/research/top-ten-global-health-supply-chain-issues-perspectives-field
Rosales, C. R., Magazine, M., & Rao, U. (2014). Point‐of‐Use Hybrid Inventory Policy for Hospitals. Decision Sciences, 45(5), 913-937. Retrieved from https://scholars.opb.msu.edu/en/publications/point-of-use-hybrid-inventory-policy-for-hospitals-2
Sarker, B. R. (2014). Consignment stocking policy models for supply chain systems: A critical review and comparative perspectives. International Journal of Production Economics, 155, 52-67. Retrieved from https://econpapers.repec.org/article/eeeproeco/v_3a155_3ay_3a2014_3ai_3ac_3ap_3a52-67.htm
Unger, S., & Landis, A. (2016). Assessing the environmental, human health, and economic impacts of reprocessed medical devices in a Phoenix hospital’s supply chain. Journal of Cleaner Production, 112, 1995-2003. Retrieved from https://asu.pure.elsevier.com/en/publications/assessing-the-environmental-human-health-and-economic-impacts-of–2
Uthayakumar, R., & Priyan, S. (2013). Pharmaceutical supply chain and inventory management strategies: optimization for a pharmaceutical company and a hospital. Operations Research for Health Care, 2(3), 52-64. Retrieved from http://www.sciencedirect.com/science/article/pii/S2211692313000155
Wager, K. A., Lee, F. W., & Glaser, J. P. (2017). Health care information systems: a practical approach for health care management. John Wiley & Sons. Retrieved from https://www.amazon.com/Health-Care-Information-Systems-Management/dp/0470387807
Wamba, S. F., Anand, A., & Carter, L. (2013). A literature review of RFID-enabled healthcare applications and issues. International Journal of Information Management, 33(5), 875-891. Retrieved from https://pdfs.semanticscholar.org/a1e6/bfc6b337962165eac409a03fd65769d625eb.pdf